Intelligent Decision Support for Medication Review

  • Ivan Bindoff
  • Peter Tenni
  • Byeong Ho Kang
  • Gregory Peterson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4303)


This paper examines an implementation of a Multiple Classification Ripple Down Rules system which can be used to provide quality Decision Support Services to pharmacists practicing medication reviews (MRs), particularly for high risk patients. The system was trained on 84 genuine cases by an expert in the field; over the course of 15 hours the system had learned 197 rules and was considered to encompass around 60% of the domain. Furthermore, the system was found able to improve the quality and consistency of the medication review reports produced, as it was shown that there was a high incidence of missed classifications under normal conditions, which were repaired by the system automatically.


Knowledge Acquisition Medication Review Case Base Reasoning Multiple Classification Wrong Classification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Peterson, G.: Continuing evidence of inappropriate medication usage in the elderly. In: Australian Pharmacist, p. 2 (2004)Google Scholar
  2. 2.
    Bates, D., et al.: Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. JAMA 274, 29–34 (1995)Google Scholar
  3. 3.
    Peterson, G.: The future is now: the importance of medication review. In: Australian Pharmacist, pp. 268–275 (2002)Google Scholar
  4. 4.
    Rigby, D.: The challenge of change - establishing an HMR service in the pharmacy. In: Australian Pharmacist, pp. 214–217 (2004)Google Scholar
  5. 5.
    Kinrade, W.: Review of Domiciliary Medication Management Review Software. Pharmacy Guild of Australia, p. 77 (2003)Google Scholar
  6. 6.
    Aamodt, A., Plaza, E.: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AICom - Artificial Intelligence Communications, 39–59 (1994)Google Scholar
  7. 7.
    Compton, P., et al.: Knowledge Acquisition without Analysis. In: Knowledge Acquisition for Knowledge-Based Systems, Springer, Heidelberg (1993)Google Scholar
  8. 8.
    Tenni, P., et al. to I. Bindoff (2005)Google Scholar
  9. 9.
    Bonner, C.: MediFlags (2005)Google Scholar
  10. 10.
    Compton, P., Jansen, R.: A philosophical basis for knowledge acquisition. In: European Knowledge Acquisition for Knowledge-Based Systems, Paris (1989)Google Scholar
  11. 11.
    Rivest, R.: Learning Decision Lists. Machine Learning, 229–246 (1987)Google Scholar
  12. 12.
    Kang, B., Compton, P., Preston, P.: Multiple Classification Ripple Down Rules (1994)Google Scholar
  13. 13.
    Kolodner, J., Simpson, R., Sycara-Cyranski, K.: A Process Model of Cased-based Reasoning in Problem Solving. In: International Joint Conference on Artificial Intelligence, Morgan Kaufmann, Los Angeles (1985)Google Scholar
  14. 14.
    Kolodner, J.L.: Special Issue on Case-Based Reasoning - Introduction. Machine Learning 10(3), 195–199 (1993)CrossRefGoogle Scholar
  15. 15.
    Kang, B., Compton, P.: A Maintenance Approach to Case Based Reasoning (1994)Google Scholar
  16. 16.
    Kang, B., Compton, P., Preston, P.: Multiple Classification Ripple Down Rules: Evaluation and Possibilities. In: AIII-Sponsored Banff Knowledge Acquisition for Knowledge-Based Systems, Banff (1995)Google Scholar
  17. 17.
    Bindoff, I.: An Intelligent Decision Support System for Medication Review. In: Computing, University of Tasmania: Hobart, p. 65 (2005)Google Scholar
  18. 18.
    Preston, P., Edwards, G., Compton, P.: A 2000 Rule Expert System Without a Knowledge Engineer. In: AIII-Sponsored Banff Knowledge Acquisition for Knowledge-Based Systems, Banff (1994)Google Scholar
  19. 19.
    Compton, P., Jansen, R.: Cognitive aspects of knowledge acquisition. In: AAAI Spring Consortium, Stanford (1992)Google Scholar
  20. 20.
    Tenni, P. to I. Bindoff (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ivan Bindoff
    • 1
  • Peter Tenni
    • 2
  • Byeong Ho Kang
    • 1
  • Gregory Peterson
    • 2
  1. 1.School of ComputingUniversity of Tasmania 
  2. 2.Unit for Medical Outcomes and Research EvaluationsUniversity of Tasmania 

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